Data Cleansing: The Importance of CRM Data Integrity
If you’re a business owner, you probably spend a lot of time collecting customer data. Customer data is important for marketing, communication, and improving the customer experience. But it only works if it’s accurate. That’s why it’s important to maintain CRM data integrity.
Whether your business is online or brick and mortar, you know the importance of collecting complete customer data. You need it to deliver your products and services, market to new and existing customers, communicate important updates, and improve your customers’ experiences.
There are two major problems when it comes to collecting and managing customer data:
- Accurate data is not always entered into your database.
- The data you collect decays over time.
You can imagine the monetary ramifications, but we’ll go into more detail later. Just remember that your marketing is only as strong as your data.
What is CRM Data Integrity?
Customer relationship management (CRM) refers to the analysis and utilization of customer data. Analysis of customer data determines how that data is used to interact with existing, past, and potential customers.
Data integrity refers to the accuracy of that data. Like we mentioned before, there are two main ways your customer data can be problematic. First, information can be entered incorrectly. Second, data becomes outdated over time.
So how do you fix these problems?
How to Maintain CRM Data Integrity
When data is entered manually, there is always room for error. Information can be mistyped, fields can be overlooked, complete information may not be readily available. Because of this, information entered either by you or by a sales rep should be validated.
The same is true of data entered on web forms. Users make mistakes both intentionally and unintentionally. There could be a typo, information entered into the wrong field, fields left blank, or fake information submitted to avoid further marketing materials or to protect privacy.
When you consider all of that room for error, do you think you should immediately use the data you collect by these methods? Heck no!
Imagine calling the wrong number or addressing an email to an incorrect or misspelled name. It hurts your image as a business and could make you liable for TCPA fines if you market to someone who hasn’t opted in.
Then there’s the time and money you waste reaching out to invalid email addresses, calling disconnected phone numbers, and sending undeliverable mail and packages to incorrect addresses.
Input validation allows only approved data to be submitted on forms. This is your first line of defense against customers entering erroneous, fake, and incomplete data. Learn how to use validation error messages to improve web form submissions here.
Unintentional alterations to existing data can occur when data moves from one department to another, from one device to another, or when updates are run. Validating data after any of these routines can help catch and correct resulting errors to data that was once clean, or initially validated (more on this later).
There are three ways to validate data: data validation API, batch data processing, and data append.
1. Data Validation API
A data validation API checks data at the point of entry, validating form entries in real time. Integrating an external data validation service into your data management and processing systems allows you to use your data immediately.
The alternative is to segregate new data and batch process it before integrating it into your main database for use.
2. Batch Data Processing
Without a data processing system for data integration, you can upload your data to your external data validation service manually via batch data processing. Then, reload the returned file into your database to start using your verified data.
3. Data Append
While validation typically involves identifying and fixing incorrect data, data append fills in gaps in data. Say you have a customer’s address, but not phone number. Data validation API and batch data processing can find this information and append, or add, it to your list.
To aid in the validation process, it’s a good idea to avoid as many errors as possible early on. The best way to do this is to lean toward automation over manual entry.
The greatest thing about using a data validation API is that it automates your systems and reduces the need for manual data entry, therefore reducing the chances for error. Automated data validation takes place both at the point of entry and throughout the lifecycle of the data.
Problem number one of data collection is the entry of incorrect, invalid, and incomplete data. Problem number two is data decay.
About 30% of customer data decays each year. Data decays when it changes. Customers move to new addresses, switch phone carriers and get new phone numbers, they change jobs and their old email addresses are abandoned.
Continuing to market using this outdated data is a waste of time and resources. And you could face fines for marketing to phone numbers that get reassigned. To prevent these errors and waste, you should regularly cleanse your data.
Data cleansing (also referred to as data scrubbing) involves ridding duplicate entries, fixing incorrect data, and completing missing data. Again, you can do this manually using a batch append tool or automate the process using an API.
We recommend protecting your data by automating as much of the process as possible. Check out some CRM data cleansing best practices here.
What Does Bad Data Cost You?
It goes without saying. Bad data is wasteful. The more bad data you have, the more time and resources you must spend to fix it. Otherwise, you risk your image, your customer acquisition, and your customer retention. No surprises there. But let’s look at some numbers.
Say, for instance, you have 700,000 records. Say 80% of that data is from existing customers from the previous year. Thirty percent of that (168k) is no longer valid; it has become outdated, or decayed. The other 20% of your records is new data that you’ve accumulated from new leads. About 60% of that (84k) is false information consumers intentionally provided!
That means that unless validated or cleaned, 36% of your data (252k) is no good. Now, how much will it cost you to market to this segment? Let’s take SMS for example. If it costs an average of about $0.0067 to send a text message, and you send a message to 252k numbers, you’ve wasted $1,688.40.
And that’s for ONE text message. That number only represents one part of one campaign on one platform. If that campaign requires that you send one text message a month, you’re looking at $20,260.80 in one year spent on messages that did not reach their intended recipient.
Alternatively, let’s consider the opportunities that present themselves when you collect and manage good data. Over 75% of marketers have reported on how their campaigns directly influence revenue. However, this influence is affected by the quality of their data.
Utilize Multiple Marketing Platforms
After validating and appending your customer data, it’s time for data enhancement. Data enhancement combines data silos to create unified customer profiles.
Rather than keeping information segregated for use with each separate marketing channel, you can use data enhancement to create a single CRM database.
This makes your CRM data easier to search, update, and use. All customer data is then available to all of your teams, regardless of how they’re contacting customers. About 73% of marketers with a CRM system, for example, use it to share a customer view between their service and sales teams.
This way, you can supplement one channel with another and increase your reach. Social media, email, phone messaging, and even direct mail marketing are alive and well. Each has its benefits, but they all work best when paired with other channels.
Without clean, complete data you miss out on these marketing opportunities or risk botching one or another.
Bring in New Customers
With a strong CRM, you can analyze the data you collect to make better marketing decisions to reach new customers. You can identify trends to better direct your marketing.
Your audience might be specific to a geographic area, demographic, interests, habits, etc. This is all information you can gather once you’ve properly collected data from existing customers. You can read more about customer data best practices here.
Retain Existing Customers
According to smile.io, the average ecommerce store spends about 80% of its marketing budget on customer acquisition when 41% of its revenue is generated by only 8% of its existing customers. Furthermore, when customers purchase from you once, they are 27% more likely to purchase again. That number increases after each subsequent purchase.
So how do you use this to your advantage? Use your CRM data! Personalize further marketing to those customers to match their demographic, their interests, and their habits to increase the chance of him purchasing again.
However, you can only effectively reach these customers if your data is complete and up to date. Without it, look at all of the opportunities you miss out on!
Improve the Customer Experience
Additionally, ease and convenience are paramount. If it’s not easy to access your products and services or it’s a hassle to communicate with you when there’s an issue, you’re likely to miss out on a sale and lose a customer.
The more organized you are, the less errors you will make, and the more your customers will trust you and continue to do business with you. Consider custom API integration to improve your customer experience.
The Bottom Line
You can’t function without good data, and with the many resources and tools available to you, why wouldn’t you invest in CRM data integrity? The cost to verify and clean your data benefits your business by strengthening your leads and increasing your chance of a sale. Not to mention the fines you avoid by only marketing to addresses and numbers of customers who knowingly opt in.
The alternative is wasted money marketing to bad data. If the money is going to go somewhere, it’s best to make sure it’s money well-spent. Try Searchbug’s batch data processing and data append tools today!Learn more